Care Needs and Migration: Household Determinants of Internal Labour Migration in Vietnam
Bibliographic record
Abstract
Migration stands as a livelihood strategy for households in Southeast Asia. Recent literature calls for the study of migration at the household level and for the consideration of care needs among the determinants of migration. Based on the case of Vietnam, this article contributes to past research by providing a longitudinal analysis of how household care needs may influence the use of internal migration as a livelihood strategy. Using a household life-course perspective that recognizes how family care needs evolve over time, this article tests if care needs influence the propensity for a household to have one or more new member-out-migrants over time. We operationalize care needs through the household dependency ratio, health care and education expenditures. Multivariate analyses are based on longitudinal data from three passages of the Vietnam Living Standards Survey of 2010, 2012, and 2014. Results indicate that households needing to cover costs of children’s education are more likely to engage in migration than those with health care needs. These results reinforce the idea that migration requires certain conditions to occur and that the immediate care needs that require co-presence tend to prevent, rather than incite, migration at the household level. Overall, the analysis indicates that evolving care needs and household members’ capacities to provide for modify the way households organize and deploy their workforce over space and time.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".